Let’s define some vectors which can be used for demonstrations:
manyNumbers <- sample( 1:1000, 20 )
manyNumbers
[1] 333 117 210 629 187 918 54 237 616 823 646 541 9 618 919 365 180 765 923 99
manyNumbersWithNA <- sample( c( NA, NA, NA, manyNumbers ) )
manyNumbersWithNA
[1] 823 NA 99 618 919 765 646 365 541 54 180 9 117 629 333 918 616 210 NA 187 NA 923 237
duplicatedNumbers <- sample( 1:5, 10, replace = TRUE )
duplicatedNumbers
[1] 4 5 3 1 4 4 1 1 5 3
letters
[1] "a" "b" "c" "d" "e" "f" "g" "h" "i" "j" "k" "l" "m" "n" "o" "p" "q" "r" "s" "t" "u" "v" "w" "x" "y" "z"
LETTERS
[1] "A" "B" "C" "D" "E" "F" "G" "H" "I" "J" "K" "L" "M" "N" "O" "P" "Q" "R" "S" "T" "U" "V" "W" "X" "Y" "Z"
mixedLetters <- c( sample( letters, 5 ), sample( LETTERS, 5 ) )
mixedLetters
[1] "m" "g" "q" "s" "v" "B" "L" "F" "H" "X"
manyNumbersWithNA instead of manyNumbers.all( manyNumbers <= 1000 )
[1] TRUE
all( manyNumbers <= 500 )
[1] FALSE
any( manyNumbers > 1000 )
[1] FALSE
any( manyNumbers > 500 )
[1] TRUE
all( !is.na( manyNumbers ) )
[1] TRUE
any( is.na( manyNumbers ) )
[1] FALSE
Input: logical vector Output: vector of numbers (positions)
which( manyNumbers > 900 )
[1] 6 15 19
which( manyNumbersWithNA > 900 )
[1] 5 16 22
which( is.na( manyNumbersWithNA ) )
[1] 2 19 21
manyNumbers[ manyNumbers > 900 ] # indexing by logical vector
[1] 918 919 923
manyNumbers[ which( manyNumbers > 900 ) ] # indexing by positions
[1] 918 919 923
somePositions <- which( manyNumbers > 900 )
manyNumbers[ somePositions ]
[1] 918 919 923
"A" %in% LETTERS
[1] TRUE
c( "X", "Y", "Z" ) %in% LETTERS
[1] TRUE TRUE TRUE
all( c( "X", "Y", "Z" ) %in% LETTERS )
[1] TRUE
all( mixedLetters %in% LETTERS )
[1] FALSE
any( mixedLetters %in% LETTERS )
[1] TRUE
mixedLetters[ mixedLetters %in% LETTERS ]
[1] "B" "L" "F" "H" "X"
mixedLetters[ !( mixedLetters %in% LETTERS ) ]
[1] "m" "g" "q" "s" "v"
manyNumbers %in% 300:600
[1] TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE FALSE FALSE FALSE TRUE FALSE FALSE
[19] FALSE FALSE
which( manyNumbers %in% 300:600 )
[1] 1 12 16
sum( manyNumbers %in% 300:600 )
[1] 3
NAsif_else( manyNumbersWithNA >= 500, "large", "small" )
[1] "large" NA "small" "large" "large" "large" "large" "small" "large" "small" "small" "small" "small" "large"
[15] "small" "large" "large" "small" NA "small" NA "large" "small"
if_else( manyNumbersWithNA >= 500, "large", "small", "UNKNOWN" )
[1] "large" "UNKNOWN" "small" "large" "large" "large" "large" "small" "large" "small" "small"
[12] "small" "small" "large" "small" "large" "large" "small" "UNKNOWN" "small" "UNKNOWN" "large"
[23] "small"
# here integer 0L is needed instead of real 0.0
# manyNumbersWithNA contains integer numbers and the method complains
if_else( manyNumbersWithNA >= 500, manyNumbersWithNA, 0L )
[1] 823 NA 0 618 919 765 646 0 541 0 0 0 0 629 0 918 616 0 NA 0 NA 923 0
unique( duplicatedNumbers )
[1] 4 5 3 1
unique( c( NA, duplicatedNumbers, NA ) )
[1] NA 4 5 3 1
duplicated( duplicatedNumbers )
[1] FALSE FALSE FALSE FALSE TRUE TRUE TRUE TRUE TRUE TRUE
which.max( manyNumbersWithNA )
[1] 22
manyNumbersWithNA[ which.max( manyNumbersWithNA ) ]
[1] 923
which.min( manyNumbersWithNA )
[1] 12
manyNumbersWithNA[ which.min( manyNumbersWithNA ) ]
[1] 9
range( manyNumbersWithNA, na.rm = TRUE )
[1] 9 923
manyNumbersWithNA
[1] 823 NA 99 618 919 765 646 365 541 54 180 9 117 629 333 918 616 210 NA 187 NA 923 237
sort( manyNumbersWithNA )
[1] 9 54 99 117 180 187 210 237 333 365 541 616 618 629 646 765 823 918 919 923
sort( manyNumbersWithNA, na.last = TRUE )
[1] 9 54 99 117 180 187 210 237 333 365 541 616 618 629 646 765 823 918 919 923 NA NA NA
sort( manyNumbersWithNA, na.last = TRUE, decreasing = TRUE )
[1] 923 919 918 823 765 646 629 618 616 541 365 333 237 210 187 180 117 99 54 9 NA NA NA
manyNumbersWithNA[1:5]
[1] 823 NA 99 618 919
order( manyNumbersWithNA[1:5] )
[1] 3 4 1 5 2
rank( manyNumbersWithNA[1:5] )
[1] 3 5 1 2 4
sort( mixedLetters )
[1] "B" "F" "g" "H" "L" "m" "q" "s" "v" "X"
manyDuplicates <- sample( 10:15, 10, replace = TRUE )
rank( manyDuplicates )
[1] 5.0 7.5 2.0 10.0 2.0 9.0 2.0 5.0 7.5 5.0
rank( manyDuplicates, ties.method = "min" )
[1] 4 7 1 10 1 9 1 4 7 4
rank( manyDuplicates, ties.method = "random" )
[1] 4 8 1 10 2 9 3 5 7 6
v <- c( -1, -0.5, 0, 0.5, 1, rnorm( 10 ) )
v
[1] -1.00000000 -0.50000000 0.00000000 0.50000000 1.00000000 -0.63222395 -0.08492404 -1.57677352 1.33507263
[10] -0.66400970 -1.03485318 1.90646008 -0.62232902 -0.94611470 0.67538853
round( v, 0 )
[1] -1 0 0 0 1 -1 0 -2 1 -1 -1 2 -1 -1 1
round( v, 1 )
[1] -1.0 -0.5 0.0 0.5 1.0 -0.6 -0.1 -1.6 1.3 -0.7 -1.0 1.9 -0.6 -0.9 0.7
round( v, 2 )
[1] -1.00 -0.50 0.00 0.50 1.00 -0.63 -0.08 -1.58 1.34 -0.66 -1.03 1.91 -0.62 -0.95 0.68
floor( v )
[1] -1 -1 0 0 1 -1 -1 -2 1 -1 -2 1 -1 -1 0
ceiling( v )
[1] -1 0 0 1 1 0 0 -1 2 0 -1 2 0 0 1
heights <- c( Amy = 166, Eve = 170, Bob = 177 )
heights
Amy Eve Bob
166 170 177
names( heights )
[1] "Amy" "Eve" "Bob"
names( heights ) <- c( "AMY", "EVE", "BOB" )
heights
AMY EVE BOB
166 170 177
heights[[ "EVE" ]]
[1] 170
expand_grid( x = c( 1:3, NA ), y = c( "a", "b" ) )
# A tibble: 8 × 2
x y
<int> <chr>
1 1 a
2 1 b
3 2 a
4 2 b
5 3 a
6 3 b
7 NA a
8 NA b
combn( c( "a", "b", "c", "d", "e" ), m = 2, simplify = TRUE )
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] "a" "a" "a" "a" "b" "b" "b" "c" "c" "d"
[2,] "b" "c" "d" "e" "c" "d" "e" "d" "e" "e"
combn( c( "a", "b", "c", "d", "e" ), m = 3, simplify = TRUE )
[,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10]
[1,] "a" "a" "a" "a" "a" "a" "b" "b" "b" "c"
[2,] "b" "b" "b" "c" "c" "d" "c" "c" "d" "d"
[3,] "c" "d" "e" "d" "e" "e" "d" "e" "e" "e"
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